Multi-Objective Distribution System Planning Considering Non-Utility-Owned Distributed Generation and CO2 Emissions Costs

M. A. Mejia, J. Franco, Leonardo H. Macedo, G. Muñoz-Delgado, J. Contreras
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Abstract

Distribution systems planning (DSP) has become increasingly challenging due to the growing adoption of renewable distributed generation (DG) aimed at reducing CO2 emissions, particularly when the utility does not own these units. Therefore, this paper proposes a multi-objective stochastic strategy for DSP that considers non-utility-owned renewable DG. Under this approach, the utility makes investment decisions for assets such as conductors and voltage control equipment. Furthermore, the utilization of a multi-objective approach enables a sensitivity analysis, which assists both the utility and DG owner in reaching a consensus on the type, size, and location of renewable DG units. The strategy proposes minimizing the net present value of the investment and operational costs for both parties, with the additional goal of reducing the cost of CO2 emissions from the network. A scenario-based stochastic programming framework is used to characterize the behavior of uncertain parameters. The model is written in the AMPL language and solved using the CPLEX solver. Tests are conducted using a 69-node system, revealing that the total costs for both parties vary depending on the size and location of the DG as well as the cost of energy sold from the DG to the network.
考虑非公用事业分布式发电和CO2排放成本的多目标配电系统规划
配电系统规划(DSP)变得越来越具有挑战性,因为越来越多的可再生分布式发电(DG)旨在减少二氧化碳排放,特别是当公用事业公司不拥有这些设备时。因此,本文提出了一种考虑非公用事业拥有的可再生DG的DSP多目标随机策略。在这种方法下,公用事业公司对导体和电压控制设备等资产做出投资决策。此外,利用多目标方法可以进行敏感性分析,这有助于公用事业公司和DG所有者就可再生DG机组的类型、大小和位置达成共识。该战略建议将双方的投资净现值和运营成本最小化,并提出降低电网二氧化碳排放成本的额外目标。采用基于场景的随机规划框架来描述不确定参数的行为。该模型采用AMPL语言编写,采用CPLEX求解器求解。使用69个节点的系统进行测试,揭示双方的总成本取决于DG的大小和位置,以及从DG出售给网络的能源成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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